How To Read Excel File In Databricks Using Pandas

To read an Excel file in Databricks using Pandas, you can follow these steps:

1. Install Required Libraries

• Ensure that the `openpyxl` library is installed in your Databricks environment. This library is necessary for Pandas to read Excel files. You can install it by navigating to your Databricks cluster, clicking on “Libraries”, and then “Install New”. Select PyPI and enter `openpyxl` as the package name.

2. Import Libraries

• In your Databricks notebook, import the necessary libraries:
  • python
    import pandas as pd

3. Specify File Path

• Provide the path to your Excel file. The file should be accessible from the Databricks environment. If your file is stored in Databricks’ DBFS (Databricks File System), you will use a path like `/dbfs/mnt/…`.

4. Read the Excel File

• Use the `pandas.read_excel()` function to read the Excel file into a Pandas DataFrame. You may need to specify the engine as `openpyxl` if the file is in `.xlsx` format:
  • python
    df = pd.read_excel(‘/dbfs/mnt/your_file_path.xlsx’, engine=’openpyxl’)

5. Data Manipulation

• Once the Excel file is read into a DataFrame, you can perform various data manipulation operations using Pandas functions, such as filtering, sorting, and aggregating data.

6. Convert to Spark DataFrame (Optional)

• If you need to perform operations using Spark, you can convert the Pandas DataFrame to a Spark DataFrame:
  • python
    spark_df = spark.createDataFrame(df)

You can efficiently read and manipulate Excel files in Databricks using Pandas.

This method is particularly useful for handling smaller datasets or when specific Pandas functionalities are required.